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Article published In:
Target
Vol. 35:1 (2023) ► pp.34–62

Source language difficulties in learner translation

Evidence from an error-annotated corpus

ORCID logo | University of Wolverhampton
| University of Tyumen
| Lomonosov Moscow State University
| University of Wolverhampton

This study uses an error-annotated, mass-media subset of a sentence-aligned, multi-parallel learner translator corpus to reveal source-language items that are challenging in English–Russian translation. Our data includes multiple translations of the most challenging source sentences, drawn from a large collection of student translations on the basis of error statistics. This sample was subjected to manual contrastive-comparative analysis, which resulted in a list of English items that were difficult for students. The outcome of the analysis was compared to the topics discussed in translation textbooks that are recommended for BA and specialist-degree students in Russia. We discuss items that deserve more prominence in training as well as items that call for improvements to traditional learning activities. This study presents evidence that a more empirically motivated design of the practical translation syllabus as part of translator education is required.

Keywords: translator education, learner translator corpus, translation error analysis, multi-parallel corpus, error-prone source items, translation competence
Article outline
  • 1.Introduction
  • 2.Related work
    • 2.1Error-annotated learner translator corpora
    • 2.2Error annotation for identification of error-prone SL items
  • 3.Data
    • 3.1Textbooks on translation practice
    • 3.2Learner translations
      • 3.2.1Filtering
      • 3.2.2Error annotation
      • 3.2.3Downsizing to a non-random sample for manual analysis
  • 4.Method and results
    • 4.1Textbook analysis
    • 4.2Learner data: Manual analysis
  • 5.Discussion
    • 5.1Observed SL-related problems underrepresented in textbooks
    • 5.2Cases of persistent problems: SL items inadequately learnt
  • 6.Conclusion
  • Acknowledgements
  • Notes
  • References
Published online: 3 June 2022
DOI logo
https://doi.org/10.1075/target.20189.kun
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